{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00183178","sets":["1164:3865:9090:9233"]},"path":["9233"],"owner":"11","recid":"183178","title":["リアルタイム人口を用いたStacked denoising Autoencoderによるタクシー将来需要予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-08-22"},"_buckets":{"deposit":"605d1acd-ec03-4a87-a456-867dc109d36b"},"_deposit":{"id":"183178","pid":{"type":"depid","value":"183178","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"リアルタイム人口を用いたStacked denoising Autoencoderによるタクシー将来需要予測","author_link":["401209","401213","401208","401212","401210","401211"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"リアルタイム人口を用いたStacked denoising Autoencoderによるタクシー将来需要予測"},{"subitem_title":"Real-Time Population based Taxi Demand Forecast using Stacked denoising Autoencoders","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"IoT","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2017-08-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NTT DOCOMO, INC.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, INC.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, INC.","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/183178/files/IPSJ-MBL17084021.pdf","label":"IPSJ-MBL17084021.pdf"},"date":[{"dateType":"Available","dateValue":"2019-08-22"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MBL17084021.pdf","filesize":[{"value":"451.1 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"35"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"c24e032b-d101-4560-bfcd-a16460b4ad74","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2017 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"石黒, 慎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"菊地, 悠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"深澤, 佑介"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shin, Ishiguro","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Haruka, Kikuchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yusuke, Fukazawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11851388","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8817","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"タクシーの効率的な運行には，運転手に乗客に関する様々な情報を与えることが有効である．高効率なタクシー運行は，タクシー事業の収益向上に繋がるだけでなく，乗客が素早くタクシーに乗車することにも効果があり，社会全体の交通の効率化を期待できる．本稿では Stacked denoising Autoencoder を用いたタクシー将来需要の予測とそれに基づいた運行支援手法を提案する．提案法では，タクシー運行データ，リアルタイム人口統計データおよび雨量データを用いることで，MAPE による評価により，26.77 % の誤差で予測が可能であることを示す．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告モバイルコンピューティングとパーベイシブシステム（MBL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2017-08-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"21","bibliographicVolumeNumber":"2017-MBL-84"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"updated":"2025-01-20T03:47:12.476772+00:00","created":"2025-01-19T00:50:43.567726+00:00","id":183178}